The world population is ageing and while many older people are in
good health, others have increasing numbers of comorbidities. The
presence of multiple health conditions can raise methodological
challenges when modelling health care interventions. One instance is
when determining the effect on the underlying health related quality of
life when alleviating or avoiding a particular condition. Historically,
health care modellers have estimated the preference-based utility
values required for the comorbidity using the utility values obtained
from cohorts with the individual conditions. Research conducted within
HEDS has shown that the alternative methods typically used produce very
different utility values.
Research in this area is
continuing to be developed within HEDS and a project funded by
Bristol-Myers Squibb Pharmaceuticals Limited will examine alternative
methods of predicting the effects on quality of life due to
comorbidities. The proposed approach will examine the use of response
mapping to predict the preference-based utility values for
comorbidities. Unlike the methods typically used, which combine the
overall summary preference-based utility values, response mapping
utilises all the knowledge and information from across the full health
profile using data from the health dimensions. Due for completion at
the end of this year, the results of this research will contribute to
the sparse literature in this area and is expected to identify
additional research questions.
Roberta Ara is leading this research project.
Photo credit: xavi talleda via Flickr Creative Commons